Solved problems. Proven solutions.

Build a consistent, verifiable local entity across first-party and independent sources. AI systems need evidence that the business exists, does the claimed work, and is relevant to the requested market. 1. Keep name, location/service area, contact information, services, leadership, and official profiles consistent. 2. Publish detailed service and location p…

Create a consistent identity layer across the first-party site and authoritative external references. On the site, maintain a clear organization/about page with the canonical brand name, what the company does, primary website, headquarters or service model, leadership where appropriate, contact information, founding context, and links to official profiles.…

Treat structured data as a graph of recurring real-world entities, not as a collection of independent snippets. Assign stable @id values to entities that persist across pages. For example, the organization can use a canonical homepage fragment ID, a real location can use its location-page URL plus an entity fragment, and an author can use the professional p…

Build repeated, verifiable relationships between entities rather than relying on keyword frequency. On the site, connect the organization to identifiable authors/experts, products/services, research, documentation, locations, and topic hubs. Use clear author bios, About pages, stable profile URLs, and internal links that show who is responsible for which ex…

Treat structured data as a machine-readable reinforcement layer, not a substitute for content, authority, or corroboration. Schema can make entity relationships explicit: who published an article, which organization owns a brand, where a local business is located, which product has a given identifier, what an FAQ or how-to section represents, and how pages…

Treat the incorrect answer as an entity-resolution problem. List each wrong or ambiguous fact and identify the likely entity it was confused with. Then search the web for sources supporting both the correct and incorrect versions. Build an entity evidence map covering the official website, About/Contact/Location pages, Organization/LocalBusiness schema, maj…

Start with the information system that AI products can retrieve and corroborate, not with platform-specific hacks. 1. Define the entities. Establish the brand, products/services, people, locations, and relationships you want machines to understand. Use stable names, URLs, descriptions, and identifiers. 2. Build source consistency. Your website, profiles, au…

Separate syntax validation from semantic validation. First confirm the JSON-LD is valid and uses supported Schema.org types/properties. Then verify that the markup describes content visibly present on the page. Search engines may ignore technically valid markup that exaggerates, invents, or conflicts with the user-visible page. Check entity identity careful…

Think in terms of entity evidence and corroboration rather than writing special text for an AI bot. The business should be easy to identify consistently across its own site and independent sources. On the site, establish a clear entity home. Include the official business name, concise description, primary services or products, service geography where releva…